Reversible symmetric nonexpansive convolution: An effective image boundary processing for M-channel lifting-based linear-phase filter banks

Taizo Suzuki, Masaaki Ikehara

    Research output: Contribution to journalArticle

    5 Citations (Scopus)

    Abstract

    We present an effective image boundary processing for M-channel (M ∈ ℕ, M ≥ 2) lifting-based linear-phase filter banks that are applied to unified lossy and lossless image compression (coding), i.e., lossy-to-lossless image coding. The reversible symmetric extension we propose is achieved by manipulating building blocks on the image boundary and reawakening the symmetry of each building block that has been lost due to rounding error on each lifting step. In addition, complexity is reduced by extending nonexpansive convolution, called reversible symmetric nonexpansive convolution, because the number of input signals does not even temporarily increase. Our method not only achieves reversible boundary processing, but also is comparable with irreversible symmetric extension in lossy image coding and outperformed periodic extension in lossy-to-lossless image coding.

    Original languageEnglish
    Article number6775296
    Pages (from-to)2744-2749
    Number of pages6
    JournalIEEE Transactions on Image Processing
    Volume23
    Issue number6
    DOIs
    Publication statusPublished - 2014 Jun

    Keywords

    • Lifting-based linear-phase filter bank (L-LPFB)
    • lossyto-lossless image coding
    • reversible symmetric extension (RevSE)
    • reversible symmetric nonexpansive convolution (RevSNEC)

    ASJC Scopus subject areas

    • Software
    • Computer Graphics and Computer-Aided Design

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